The present invention relates generally to the field of image capture, and more particularly to an image capture enhancement system using a dynamic control image.
Closed-circuit television (CCTV) is the use of one or multiple video cameras to provide surveillance or monitoring of an area within the view of the one or more video cameras. The CCTV cameras may be static, in a fixed position, or they may be dynamic with movement to pan, tilt, or zoom to provide more information on an area. The images received from CCTV cameras may be analyzed to detect and identify or recognize objects, including people. Photometric sampling techniques are known to be used in building geometric models for subject recognition in CCTV imagery.
Performing subject, and in particular facial, recognition on CCTV sources of images can be greatly enhanced by taking into account the physical geometry of the subject being identified. This information is, however, not usually directly available unless using highly specialized and expensive 3D scanning devices. Typically, in the field of facial recognition, subject geometry is estimated in software using lighting compensation models and shadow detection to estimate the orientation or pose of the subject. These techniques may suffer proportionally with variation in lighting conditions and in lower light environments such as underground stations.
The significance of lighting conditions for facial recognition is important. To perform high quality facial recognition a number of fiducial markers must be determined in order to encode the face for searching; markers such as the corners of the eyes, pupils, lips, nose, and many other more subtle points. In a controlled environment, such as an airport border control desk, the lighting is consistent, the light and subject face each other directly, removing shadows. In this situation, although 3D surface models are generated to account for subtle tilt and rotation, the surface detail is more important and accurate for determining the fiducial markers.